{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "dccf2175-df17-49db-9474-e74f004ce2bc",
   "metadata": {},
   "outputs": [],
   "source": [
    "suppressMessages(library(ArchR))\n",
    "suppressMessages(library(Seurat))\n",
    "suppressMessages(library(Signac))\n",
    "suppressMessages(library(dplyr))\n",
    "suppressMessages(library(ComplexHeatmap))\n",
    "suppressMessages(library(mclust))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "52224271-31bf-452c-a769-90dff7fcbf4b",
   "metadata": {},
   "outputs": [],
   "source": [
    "obj.atac <- readRDS(\"../data/snATAC.Rds\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "044c097e-09d9-4013-a459-d7f571946e6e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "An object of class Seurat \n",
       "560350 features across 46086 samples within 3 assays \n",
       "Active assay: RNA (19204 features, 0 variable features)\n",
       " 2 other assays present: peaks, GeneActivity\n",
       " 6 dimensional reductions calculated: scopen, umap, harmony, umap_harmony, umap_harmony_v2, pca"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "obj.atac"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "2dd470bb-23e1-483e-be2e-4aafc4d2bc33",
   "metadata": {},
   "outputs": [],
   "source": [
    "cM <- confusionMatrix(obj.atac$cell_type, obj.atac$predicted.id)\n",
    "cM <- cM / Matrix::rowSums(cM)\n",
    "\n",
    "cM <- cM[, c(\"Adipo\", \"CM\", \"Myeloid\", \"Endo\", \"Fib\", \"Pericyte\", \"Neuronal\", \"Lymphoid\", \"vSMCs\")]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "6fc26734-df42-4acd-8120-21044d11ba9e",
   "metadata": {},
   "outputs": [],
   "source": [
    "ari <- as.data.frame(adjustedRandIndex(obj.atac$cell_type, obj.atac$predicted.id))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "eaa15070-747b-47ca-af62-03f3420e6e55",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A data.frame: 1 × 1</caption>\n",
       "<thead>\n",
       "\t<tr><th scope=col>adjustedRandIndex(obj.atac$cell_type, obj.atac$predicted.id)</th></tr>\n",
       "\t<tr><th scope=col>&lt;dbl&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><td>0.9805804</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 1 × 1\n",
       "\\begin{tabular}{l}\n",
       " adjustedRandIndex(obj.atac\\$cell\\_type, obj.atac\\$predicted.id)\\\\\n",
       " <dbl>\\\\\n",
       "\\hline\n",
       "\t 0.9805804\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 1 × 1\n",
       "\n",
       "| adjustedRandIndex(obj.atac$cell_type, obj.atac$predicted.id) &lt;dbl&gt; |\n",
       "|---|\n",
       "| 0.9805804 |\n",
       "\n"
      ],
      "text/plain": [
       "  adjustedRandIndex(obj.atac$cell_type, obj.atac$predicted.id)\n",
       "1 0.9805804                                                   "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ari"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "e65eef79-6017-456a-a4ff-0ea7f135fc70",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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t6W8q5a0C8ApZqcpdQpIm6ubvsPHjB3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\n1/UAAAAASUVORK5CYII=",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 300,
       "width": 360
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "options(repr.plot.height = 5, repr.plot.width = 6)\n",
    "\n",
    "p <- Heatmap(as.matrix(cM),\n",
    "             name = \"Proportion\",\n",
    "             cluster_columns = FALSE,\n",
    "             cluster_rows = FALSE,\n",
    "             clustering_distance_rows = \"pearson\",\n",
    "             rect_gp = gpar(col = \"black\", lwd = 0.5),\n",
    "            col = paletteContinuous(\"whiteBlue\"))\n",
    "\n",
    "p"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0bab9a4d-20c6-40ac-8043-591a70df47d3",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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